Dynamic Programming Problem-Solving Questions
What is Dynamic Programming?
Dynamic Programming (DP) is an optimization technique used in computer programming to solve complex problems by breaking them down into simpler subproblems. It stores the results of subproblems to avoid redundant computations, dramatically improving efficiency.
Key Concepts in C:
- Memoization: Top-down approach using recursion and caching
- Tabulation: Bottom-up approach using iteration and table storage
- Optimal Substructure: Problems can be divided into optimal subproblems
- Overlapping Subproblems: Subproblems recur multiple times
1. Basic DP Problems
| S.No | Problem Statement | Difficulty | LeetCode | GeeksforGeeks |
|---|---|---|---|---|
| 1 | Fibonacci Number | Easy | Link | Link |
| 2 | Climbing Stairs | Easy | Link | Link |
| 3 | House Robber | Medium | Link | Link |
| 4 | Coin Change | Medium | Link | Link |
2. 2D DP Problems
| S.No | Problem Statement | Difficulty | LeetCode | GeeksforGeeks |
|---|---|---|---|---|
| 1 | Unique Paths | Medium | Link | Link |
| 2 | Minimum Path Sum | Medium | Link | Link |
| 3 | Edit Distance | Hard | Link | Link |
3. Knapsack Problems
| S.No | Problem Statement | Difficulty | LeetCode | GeeksforGeeks |
|---|---|---|---|---|
| 1 | 0/1 Knapsack | Medium | - | Link |
| 2 | Unbounded Knapsack | Medium | - | Link |
Related DP Resources
Dynamic Programming Tips for C Programmers
Best Practices
- Always start with recursive solution before optimizing
- Use memoization with static arrays for better performance
- Initialize DP tables properly with memset() in C
- Optimize space complexity by reusing arrays
Common Pitfalls
- Forgetting base cases in recursive solutions
- Incorrectly identifying subproblems
- Not handling edge cases (empty inputs, etc.)
- Memory issues with large DP tables
Related DP Resources